1163-P: Cost Effectiveness of Oral Semaglutide 14mg vs. Empagliflozin 25mg in Canada
Bibliographic record
Abstract
Background: A1C lowering was significantly greater for oral semaglutide 14 mg than empagliflozin 25 mg for patients with type 2 diabetes mellitus (T2DM) uncontrolled on metformin in the 52-week, randomized, open-label PIONEER 2 trial (NCT02863328). We estimated the cost effectiveness of oral semaglutide vs. empagliflozin in Canada from the payer and societal perspectives. Methods: Modeling methods were used to extrapolate benefits observed in PIONEER 2 to long-term costs and outcomes, including quality-adjusted life-years (QALYs), for patients treated with oral semaglutide or empagliflozin. As with analysis in other settings, the IHE-Diabetes Cohort Model (IHE-DCM) was used. The analysis was also run using the Economic and Health Outcomes microsimulation model (ECHO-T2DM). Patient baseline characteristics and treatment effects were sourced from PIONEER 2. In the model simulations, both agents were assumed discontinued and insulin initiated when A1C was >8.0%. Unit costs (CAD$) and utilities were sourced from the literature. Results: Oral semaglutide was associated with more QALYs than empagliflozin over 40 years (0.39 with IHE-DCM and 0.34 with ECHO-T2DM). The gains came with increased costs (CAD$8,202 with IHE-DCM and CAD$9,255 with ECHO-T2DM), yielding incremental cost-effectiveness ratios (ICERs) of CAD$21,115 and CAD$27,496/QALY gained, respectively, below the often-cited willingness-to-pay threshold of CAD$50,000/QALY. When productivity costs and the full societal perspective are considered, the ICERs were CAD$18,239 and CAD$19,112, respectively. Sensitivity analyses that included cost, treatment effect, time horizon and biomarker rebound assumptions generally confirmed the results. Conclusion: Two models independently found oral semaglutide to be cost-effective compared to empagliflozin over 40 years for the treatment of patients with T2DM uncontrolled on metformin in Canada. While uncommon, the use of two models can reduce decision-making uncertainty. Disclosure A.R. Liu: Employee; Self; Novo Nordisk Canada Inc. P.G. Bech: Employee; Self; Novo Nordisk Inc. Stock/Shareholder; Self; Novo Nordisk Inc. A. Fridhammar: None. A. Nilsson: None. M. Willis: Board Member; Self; The Swedish Institute for Health Economics. Consultant; Self; Janssen Global Services, LLC., Mundipharma International, Novo Nordisk A/S. Stock/Shareholder; Self; The Swedish Institute for Health Economics. S. Nuhoho: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Johnson & Johnson. Funding Novo Nordisk Canada Inc.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".